系统科学学报2024,Vol.32Issue(4) :118-125.

考虑能耗与用户效用的制造云服务调度优化

Cloud Manufacturing Service Scheduling Optimization Considering Energy Consumption and User Utility

王天日 张敏敏 张鹏志 栗继祖
系统科学学报2024,Vol.32Issue(4) :118-125.

考虑能耗与用户效用的制造云服务调度优化

Cloud Manufacturing Service Scheduling Optimization Considering Energy Consumption and User Utility

王天日 1张敏敏 2张鹏志 2栗继祖1
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作者信息

  • 1. 太原理工大学经济管理学院,山西太原 030024;山西省大数据管理与应用研究生教育创新中心,山西太原 030024
  • 2. 太原理工大学经济管理学院,山西太原 030024
  • 折叠

摘要

针对云制造环境下多用户制造任务调度问题中忽视能耗对云制造系统的影响,综合考虑云服务需求方和云服务供应方的利益,以最小化服务供应商能耗和最大化用户平均效用为目标,建立了多目标多用户任务调度模型.然后,将模拟退火算法融入带精英策略的非支配排序遗传算法(NSGA-Ⅱ),设计了一种混合多目标算法HNSGA-Ⅱ.通过算例分析验证了模型的适用性,并说明所提模型能够为云制造平台中具有不同需求的用户生成不同的调度方案.最后,利用不同规模的模拟试验,将所提算法与NSGA-Ⅱ、SPEA2算法进行比较,仿真结果说明该算法能够获得高质量的解.

Abstract

For multi-user manufacturing task scheduling problem,most research ignores the effect of energy consumption on cloud manufacturing system.Considering the interests of cloud service demanders and cloud service providers,a multi-objective multi-user task scheduling model is established to minimize energy consumption of service providers and maximize user utility.Then,a hybrid multi-objective algo-rithm HNSGAⅡ is designed by combining simulated annealing algorithm(SA)with non-dominated sorting genetic algorithm(NSGA-Ⅱ)to solve the model.By numerical example analysis,the feasibility of pro-posed model is validated,and this model can generate different scheduling schemes for users with differ-ent requirements in cloud manufacturing(CMfg)platform.Finally,compared with NSGA-Ⅱ and SPEA2 on different scale experiments,simulation results show that the proposed approach can obtain high quality solution.

关键词

云制造/多用户任务/能耗/非支配排序遗传算法/模拟退火

Key words

cloud manufacturing/multi-user task/energy consumption/non-dominated sorting ge-netic algorithm/simulated annealing

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出版年

2024
系统科学学报
太原理工大学

系统科学学报

北大核心
影响因子:0.478
ISSN:1005-6408
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